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Spatiotemporal distribution of pollutants and impact of local meteorology on source influence on pollutants’ level in a traffic air-shed in Lagos megacity, Nigeria
Pollution from vehicular emissions is a major cause of poor air quality observed in many urban and semi-urban towns and cities. As such, this study was conducted to assess air quality and the spatiotemporal distribution of vehicular and traffic-related pollutants in several air sheds of Lagos megaci...
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| Published in: | Environmental monitoring and assessment 2023-09, Vol.195 (9), p.1126-1126, Article 1126 |
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| cites | cdi_FETCH-LOGICAL-c352t-d99f2ff593cacb2686b527cd3a53851d2a60849b3747ffad6d3f85496fa898513 |
| container_end_page | 1126 |
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| container_title | Environmental monitoring and assessment |
| container_volume | 195 |
| creator | Olufemi, Ayodele P. Fawole, Olusegun G. Owoade, Oyediran K. Popoola, Olalekan A. M. Jones, Roderic L. Toyeje, Adekunle B. Abiodun, Pelumi O. Omokungbe, Opeyemi R. Abiye, Olawale E. Sunmonu, Lukman A. |
| description | Pollution from vehicular emissions is a major cause of poor air quality observed in many urban and semi-urban towns and cities. As such, this study was conducted to assess air quality and the spatiotemporal distribution of vehicular and traffic-related pollutants in several air sheds of Lagos megacity, the economic nerve centre of Nigeria. A setup of low-cost air quality sensors comprising five (5) units was deployed between November 2018 and February 2019 within traffic corridors in the heart of the city. Diurnal variation of pollutants indicated that carbon dioxide (CO
2
) peaked during the early hours of the day, total oxide (O
x
= NO
2
+O
3
) peaked at mid-day while carbon monoxide (CO) had two distinct peaks which correspond to morning and evening rush hours. Nitrogen dioxide (NO
2
) concentration peaked during evening hours. Average concentrations are NO
2
(97.1
±
9.7) ppb, O
x
(78.6
±
27.2) ppb, CO
2
(450.1
±
31.2) ppm, and CO (2285.63
±
743.7) ppb. Average concentrations of pollutants were above thresholds set by the World Health Organization (WHO) except for NO
2
which was within the range permissible limits. The implication of this is that the atmosphere is polluted due to elevated concentrations of airborne pollutants, an indication which is of both health and environmental concern. The air quality index (AQI) indicates that the quality of ambient air varies from good to very unhealthy for O
x
, and unhealthy to very unhealthy for CO, while AQI for PM
2.5
and PM
10
showed hazardous at all the sampling locations except at UNILAG where it is unhealthy for the sensitive group. For all of the sampling sites, conditional bivariate probability function (CBPF) plots show a significant agreement with the location of known pollution sources. |
| doi_str_mv | 10.1007/s10661-023-11757-x |
| format | article |
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2
) peaked during the early hours of the day, total oxide (O
x
= NO
2
+O
3
) peaked at mid-day while carbon monoxide (CO) had two distinct peaks which correspond to morning and evening rush hours. Nitrogen dioxide (NO
2
) concentration peaked during evening hours. Average concentrations are NO
2
(97.1
±
9.7) ppb, O
x
(78.6
±
27.2) ppb, CO
2
(450.1
±
31.2) ppm, and CO (2285.63
±
743.7) ppb. Average concentrations of pollutants were above thresholds set by the World Health Organization (WHO) except for NO
2
which was within the range permissible limits. The implication of this is that the atmosphere is polluted due to elevated concentrations of airborne pollutants, an indication which is of both health and environmental concern. The air quality index (AQI) indicates that the quality of ambient air varies from good to very unhealthy for O
x
, and unhealthy to very unhealthy for CO, while AQI for PM
2.5
and PM
10
showed hazardous at all the sampling locations except at UNILAG where it is unhealthy for the sensitive group. For all of the sampling sites, conditional bivariate probability function (CBPF) plots show a significant agreement with the location of known pollution sources.</description><identifier>ISSN: 0167-6369</identifier><identifier>EISSN: 1573-2959</identifier><identifier>DOI: 10.1007/s10661-023-11757-x</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Air ; Air pollution ; Air quality ; Air quality assessments ; Atmospheric Protection/Air Quality Control/Air Pollution ; Bivariate analysis ; Carbon dioxide ; Carbon monoxide ; Distribution ; Diurnal variations ; Earth and Environmental Science ; Ecology ; Ecotoxicology ; Emissions ; Environment ; Environmental Management ; Environmental monitoring ; Environmental perception ; Indoor air pollution ; Megacities ; Meteorology ; Monitoring/Environmental Analysis ; Nerves ; Nitrogen dioxide ; Outdoor air quality ; Ozone ; Particulate matter ; Pollutants ; Pollution sources ; Probability theory ; Quality assessment ; Sampling ; Spatial distribution ; Temporal distribution ; Traffic ; Urban air quality ; Vehicle emissions</subject><ispartof>Environmental monitoring and assessment, 2023-09, Vol.195 (9), p.1126-1126, Article 1126</ispartof><rights>The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c352t-d99f2ff593cacb2686b527cd3a53851d2a60849b3747ffad6d3f85496fa898513</citedby><cites>FETCH-LOGICAL-c352t-d99f2ff593cacb2686b527cd3a53851d2a60849b3747ffad6d3f85496fa898513</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2859378359/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2859378359?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,11687,27923,27924,36059,36060,44362,74666</link.rule.ids></links><search><creatorcontrib>Olufemi, Ayodele P.</creatorcontrib><creatorcontrib>Fawole, Olusegun G.</creatorcontrib><creatorcontrib>Owoade, Oyediran K.</creatorcontrib><creatorcontrib>Popoola, Olalekan A. M.</creatorcontrib><creatorcontrib>Jones, Roderic L.</creatorcontrib><creatorcontrib>Toyeje, Adekunle B.</creatorcontrib><creatorcontrib>Abiodun, Pelumi O.</creatorcontrib><creatorcontrib>Omokungbe, Opeyemi R.</creatorcontrib><creatorcontrib>Abiye, Olawale E.</creatorcontrib><creatorcontrib>Sunmonu, Lukman A.</creatorcontrib><title>Spatiotemporal distribution of pollutants and impact of local meteorology on source influence on pollutants’ level in a traffic air-shed in Lagos megacity, Nigeria</title><title>Environmental monitoring and assessment</title><addtitle>Environ Monit Assess</addtitle><description>Pollution from vehicular emissions is a major cause of poor air quality observed in many urban and semi-urban towns and cities. As such, this study was conducted to assess air quality and the spatiotemporal distribution of vehicular and traffic-related pollutants in several air sheds of Lagos megacity, the economic nerve centre of Nigeria. A setup of low-cost air quality sensors comprising five (5) units was deployed between November 2018 and February 2019 within traffic corridors in the heart of the city. Diurnal variation of pollutants indicated that carbon dioxide (CO
2
) peaked during the early hours of the day, total oxide (O
x
= NO
2
+O
3
) peaked at mid-day while carbon monoxide (CO) had two distinct peaks which correspond to morning and evening rush hours. Nitrogen dioxide (NO
2
) concentration peaked during evening hours. Average concentrations are NO
2
(97.1
±
9.7) ppb, O
x
(78.6
±
27.2) ppb, CO
2
(450.1
±
31.2) ppm, and CO (2285.63
±
743.7) ppb. Average concentrations of pollutants were above thresholds set by the World Health Organization (WHO) except for NO
2
which was within the range permissible limits. The implication of this is that the atmosphere is polluted due to elevated concentrations of airborne pollutants, an indication which is of both health and environmental concern. The air quality index (AQI) indicates that the quality of ambient air varies from good to very unhealthy for O
x
, and unhealthy to very unhealthy for CO, while AQI for PM
2.5
and PM
10
showed hazardous at all the sampling locations except at UNILAG where it is unhealthy for the sensitive group. For all of the sampling sites, conditional bivariate probability function (CBPF) plots show a significant agreement with the location of known pollution sources.</description><subject>Air</subject><subject>Air pollution</subject><subject>Air quality</subject><subject>Air quality assessments</subject><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>Bivariate analysis</subject><subject>Carbon dioxide</subject><subject>Carbon monoxide</subject><subject>Distribution</subject><subject>Diurnal variations</subject><subject>Earth and Environmental Science</subject><subject>Ecology</subject><subject>Ecotoxicology</subject><subject>Emissions</subject><subject>Environment</subject><subject>Environmental Management</subject><subject>Environmental monitoring</subject><subject>Environmental perception</subject><subject>Indoor air pollution</subject><subject>Megacities</subject><subject>Meteorology</subject><subject>Monitoring/Environmental Analysis</subject><subject>Nerves</subject><subject>Nitrogen dioxide</subject><subject>Outdoor air quality</subject><subject>Ozone</subject><subject>Particulate matter</subject><subject>Pollutants</subject><subject>Pollution sources</subject><subject>Probability theory</subject><subject>Quality assessment</subject><subject>Sampling</subject><subject>Spatial distribution</subject><subject>Temporal distribution</subject><subject>Traffic</subject><subject>Urban air quality</subject><subject>Vehicle emissions</subject><issn>0167-6369</issn><issn>1573-2959</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>M0C</sourceid><recordid>eNp9kU-OFCEYxYnRxLbHC7giceNCRv40UCzNxNFJOroYXVe-pqBlQhUlUGZ65zU8wFzMk0hPm0ziYjZAHr_38sFD6BWj54xS_a4wqhQjlAvCmJaa3D5BKya1INxI8xStKFOaKKHMc_SilBtKqdEbs0J31zPUkKob55Qh4iGUmsNuadqEk8dzinGpMNWCYRpwGGew9XgRk2346KpLOcW0P-BmKGnJ1uEw-bi4qZ2a9pDw59dvHN1PFxuAAdcM3geLIWRSvrvhqG5hn0pL3YMN9fAWfw57lwOcoWceYnEv_-1r9O3yw9eLT2T75ePVxfstsULySgZjPPdeGmHB7rjq1E5ybQcBUnSSDRwU7TZmJ_RGew-DGoTv5MYoD51pgFijN6fcOacfiyu1H0OxLkaYXFpKzztpFOWUyYa-_g-9aY-f2nT3lNCdaOsa8RNlcyolO9_POYyQDz2j_bG5_tRc35rr75vrb5tJnEylwVP7gIfoR1x_AYwHoKg</recordid><startdate>20230901</startdate><enddate>20230901</enddate><creator>Olufemi, Ayodele P.</creator><creator>Fawole, Olusegun G.</creator><creator>Owoade, Oyediran K.</creator><creator>Popoola, Olalekan A. 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M.</au><au>Jones, Roderic L.</au><au>Toyeje, Adekunle B.</au><au>Abiodun, Pelumi O.</au><au>Omokungbe, Opeyemi R.</au><au>Abiye, Olawale E.</au><au>Sunmonu, Lukman A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spatiotemporal distribution of pollutants and impact of local meteorology on source influence on pollutants’ level in a traffic air-shed in Lagos megacity, Nigeria</atitle><jtitle>Environmental monitoring and assessment</jtitle><stitle>Environ Monit Assess</stitle><date>2023-09-01</date><risdate>2023</risdate><volume>195</volume><issue>9</issue><spage>1126</spage><epage>1126</epage><pages>1126-1126</pages><artnum>1126</artnum><issn>0167-6369</issn><eissn>1573-2959</eissn><abstract>Pollution from vehicular emissions is a major cause of poor air quality observed in many urban and semi-urban towns and cities. As such, this study was conducted to assess air quality and the spatiotemporal distribution of vehicular and traffic-related pollutants in several air sheds of Lagos megacity, the economic nerve centre of Nigeria. A setup of low-cost air quality sensors comprising five (5) units was deployed between November 2018 and February 2019 within traffic corridors in the heart of the city. Diurnal variation of pollutants indicated that carbon dioxide (CO
2
) peaked during the early hours of the day, total oxide (O
x
= NO
2
+O
3
) peaked at mid-day while carbon monoxide (CO) had two distinct peaks which correspond to morning and evening rush hours. Nitrogen dioxide (NO
2
) concentration peaked during evening hours. Average concentrations are NO
2
(97.1
±
9.7) ppb, O
x
(78.6
±
27.2) ppb, CO
2
(450.1
±
31.2) ppm, and CO (2285.63
±
743.7) ppb. Average concentrations of pollutants were above thresholds set by the World Health Organization (WHO) except for NO
2
which was within the range permissible limits. The implication of this is that the atmosphere is polluted due to elevated concentrations of airborne pollutants, an indication which is of both health and environmental concern. The air quality index (AQI) indicates that the quality of ambient air varies from good to very unhealthy for O
x
, and unhealthy to very unhealthy for CO, while AQI for PM
2.5
and PM
10
showed hazardous at all the sampling locations except at UNILAG where it is unhealthy for the sensitive group. For all of the sampling sites, conditional bivariate probability function (CBPF) plots show a significant agreement with the location of known pollution sources.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1007/s10661-023-11757-x</doi><tpages>1</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0167-6369 |
| ispartof | Environmental monitoring and assessment, 2023-09, Vol.195 (9), p.1126-1126, Article 1126 |
| issn | 0167-6369 1573-2959 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_2859602015 |
| source | ABI/INFORM Global; Springer Link |
| subjects | Air Air pollution Air quality Air quality assessments Atmospheric Protection/Air Quality Control/Air Pollution Bivariate analysis Carbon dioxide Carbon monoxide Distribution Diurnal variations Earth and Environmental Science Ecology Ecotoxicology Emissions Environment Environmental Management Environmental monitoring Environmental perception Indoor air pollution Megacities Meteorology Monitoring/Environmental Analysis Nerves Nitrogen dioxide Outdoor air quality Ozone Particulate matter Pollutants Pollution sources Probability theory Quality assessment Sampling Spatial distribution Temporal distribution Traffic Urban air quality Vehicle emissions |
| title | Spatiotemporal distribution of pollutants and impact of local meteorology on source influence on pollutants’ level in a traffic air-shed in Lagos megacity, Nigeria |
| url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-11T19%3A24%3A57IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Spatiotemporal%20distribution%20of%20pollutants%20and%20impact%20of%20local%20meteorology%20on%20source%20influence%20on%20pollutants%E2%80%99%20level%20in%20a%20traffic%20air-shed%20in%20Lagos%20megacity,%20Nigeria&rft.jtitle=Environmental%20monitoring%20and%20assessment&rft.au=Olufemi,%20Ayodele%20P.&rft.date=2023-09-01&rft.volume=195&rft.issue=9&rft.spage=1126&rft.epage=1126&rft.pages=1126-1126&rft.artnum=1126&rft.issn=0167-6369&rft.eissn=1573-2959&rft_id=info:doi/10.1007/s10661-023-11757-x&rft_dat=%3Cproquest_cross%3E2859602015%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c352t-d99f2ff593cacb2686b527cd3a53851d2a60849b3747ffad6d3f85496fa898513%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2859378359&rft_id=info:pmid/&rfr_iscdi=true |